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Record W3165371148 · doi:10.1093/europace/euab116.073

Comparative effectiveness of ventricular tachycardia ablation versus escalated antiarrhythmic drug therapy by location of myocardial infarction: A sub-study of the VANISH trial

2021· article· en· W3165371148 on OpenAlexafffundabout
Michelle Samuel, Léna Rivard, Isabelle Nault, Lorne J. Gula, Vidal Essebag, Ratika Parkash, LD Sterns, Paul Khairy, JL Sapp

Bibliographic record

VenueEP Europace · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrhythmias and Treatments
Canadian institutionsUniversité de MontréalQueen Elizabeth II Health Sciences CentreWestern UniversityRoyal Jubilee HospitalMcGill University Health CentreMontreal Heart Institute
FundersFonds de Recherche du Québec - Santé
KeywordsMedicineCardiologyInternal medicineVentricular tachycardiaMyocardial infarctionAblationAmiodaroneTachycardiaAtrial fibrillation

Abstract

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Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): Fonds de recherché du Québec-Santé (FRQS) [post doctoral award for Dr. Samuel) BACKGROUND Complexity of ventricular tachycardia (VT) substrate, efficiency of lesion formation, and the size and thickness of infarction area border zones differ based on location of myocardial infarctions (MI). These differences may translate into heterogeneity in risk of events and effectiveness of treatments for VT. Small observational studies suggest that VT from inferior infarctions have higher risk of early recurrence despite smaller infarct areas. However, differential effectiveness of VT treatments based on location of MI not been definitively established. PURPOSE The objective of this sub-study of the Ventricular tachycardia AblatioN versus escalated antiarrhythmic drug therapy in ISchemic Heart disease (VANISH) randomized trial was to compare the effectiveness of VT ablation by location of MI in reducing the composite endpoint of all-cause mortality, VT storm, or appropriate ICD therapy when compared to escalated pharmacological therapy in VT patients with a prior MI. METHODS VANISH participants were categorized into 3 subgroups based on MI location: 1. Inferior (may also have MI in other locations); 2. Non-inferior (no inferior MI, all patients not in group 1); and 3. Anterior (may also have MI in other locations). Inverse probability of treatment weighting was used to balance baseline characteristics (ie. age, sex, comorbidities, medications, and the location of additional infarctions) between patients randomized to ablation or escalated therapy within each subgroup. Weighted Cox proportional hazards models were calculated separately for each subgroup. RESULTS Of 259 patients enrolled in the VANISH trial [median age 69.8 (IQR 63.0-74.2) years, 7.0% women], 135 had an inferior MI, 124 a non-inferior MI, and 83 an anterior MI. Among patients with an inferior MI, no statistically significant difference in the primary outcome was detected between patients randomized to ablation or escalated therapy [aHR 0.78 (95% CI 0.51-1.20)]. In contrast, patients with non-inferior MIs had a statistically significant reduction in the incidence of the primary outcome with ablation [aHR 0.48 (95% CI 0.27-0.86)]; which was of greater magnitude than the reduction observed in the overall results of the VANISH trial [HR 0.72 (95% CI 0.53-0.98)]. In addition, a trend towards a reduction in the primary outcome with ablation was detected in patients with anterior MIs [aHR 0.50 (95% CI 0.23-1.09)]. CONCLUSION The effectiveness of VT ablation versus escalated pharmacological therapy varies based on the location of the MI. Patients with MI scars located only in non-inferior regions of the ventricles derive greater benefit from VT ablation in reducing VT-related events. Further studies are required to explore reasons for this finding and to assess the impact of VT treatment strategies based on MI location in optimizing outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.281
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2021
Admission routes3
Has abstractyes

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